Public engineering record: 28 merged upstream PRs across the AI infrastructure stack — HuggingFace Transformers, Ray Serve, LlamaIndex, LiteLLM, axolotl, OpenAI Agents Python, Continue — plus first-party in-flight contributions to Anthropic and Microsoft codebases. Day job: PM II at Amazon, leading production ML and Gen AI programs across European operations — agentic-AI system in production (internal hackathon Most Innovative 2026), LLM-as-judge eval pipeline driving a frontier-model migration with ≥30% inference-cost reduction, 9-figure annualized impact across multiple ML launches. The AI-infrastructure work — inference, agents, post-training & fine-tuning, evaluation, alignment — happens in the OSS contributions and the day job; the operations work is where I learned how to run programs at network scale. HKU law + business, St. Gallen Master's magna cum laude, three continents, six natural languages.
Won Most Innovative Solution, 2026 at an internal Amazon AI hackathon. Built an agentic system that compresses a multi-day analyst loop into under two hours — tool-using LLM agent over schema-disciplined deterministic preprocessing of multi-GB experiment bundles, plus async AWS-native orchestration across Lambda, Step Functions, S3, and DynamoDB. Eliminates >1,400 hours/year of recurring manual work; live in production.
Owner of BRDs, launches, and the simulation + eval loops behind production ML decision systems running on a continent-scale network · hundreds of nodes. Modeled across 50+ dynamic inputs · 30+ operational metrics; millions of automated decisions per week; multi-system integration across planning, audit, and instrumentation pipelines. Two production launches in 2025 produced record reliability gains, validated on live metrics, not backtests. 9-figure annualized impact (modeled, multi-year).
Built an internal LLM-as-judge eval pipeline combining qualitative rubric scoring (6 criteria: depth, rigor, actionability, accuracy, reasoning, conciseness), quantitative metrics (latency, tokens, cost-per-call), and system metrics (tool-call accuracy, citation coverage, hallucination rate, correct-refusal rate on adversarial probes). Used it to justify and execute a frontier-model migration with explicit ROI and opportunity-cost framing — quality gains in double-digit pp on tool-call accuracy and citation coverage, hallucination rate cut by an order of magnitude, ≥30% inference-cost reduction per call. Prompt, model, and eval artifacts version-controlled; cutover atomic with predecessor model pinned for archival replay. Cost-per-call instrumented as a first-class metric in the AWS pipeline (Bedrock + Lambda + DynamoDB telemetry) alongside latency and quality. Public companion: LLM Judge Calibrator — same methodology, open-sourced.
28 merged upstream PRs across the AI infrastructure stack — LLM serving (HuggingFace Transformers, LiteLLM), compute & orchestration (Ray Serve), post-training & fine-tuning (axolotl), RAG & document AI (LlamaIndex, Docling), agents & eval (OpenAI Agents Python, Continue, Mastra). 40 in flight including first-party contributions to Anthropic (Cookbooks, Go SDK), Microsoft (Semantic Kernel), and Vercel (AI SDK security disclosure), plus active work in CrewAI, Chroma, and the agent-tooling stack.
Workspace that preserves raw transcripts, surfaces ambiguity, and runs a multi-provider eval loop across English, 中文, español, français, and português. In daily personal use.
open ↗Trilingual AI tarot in 繁體中文 / español / english. Telegram-native flows and shareable reading cards. Voice that's deadpan and a little funny.
open ↗I started in Hong Kong with dual LLB + BBA degrees at HKU, did a magna cum laude master's in Strategy & International Management at St. Gallen with a GenAI thesis on LLMs, agents, alignment, and governance, exchanged in Bogotá and Santiago, led an NGO in Guatemala, consulted out of Beijing with Accenture (market-entry strategy, Oracle ERP migration, ML revenue modeling) and Shanghai with PwC (SAP system integration), and joined Amazon as a Business Analyst in Luxembourg before rotating to the L5 PM II role in London in 2024.
The legal training shapes how I build AI: not as unconstrained generation engines, but as systems operating inside explicit rules, authorities, and validation layers. The international footprint shapes the operator habit: most of a program is translation — of constraints between teams, of intent between locales, of model behavior between markets.
The next decade of AI is won by the teams that make capability claims honest. Capabilities are the input. The eval loop is the product.
Amazon PM II. Production ML & Gen AI programs across European operations. Active OSS contributor across the AI infrastructure stack — direct in-flight contributions to Anthropic Cookbooks and the Anthropic Go SDK.
Amazon Business Analyst. Analytics, automation, and cloud-planning work across EU operations finance. Foundation for the later return to Amazon at PM II.
University of St. Gallen — MA Strategy & International Management. GenAI thesis on LLMs, agents, alignment, and governance: chained pipeline over 50K+ Reddit entries with Pydantic-coordinated agents.
The University of Hong Kong — dual LLB + BBA. Scholarships and debating-society leadership. Legal training that shapes how I build AI systems: explicit rules, authorities, validation layers.
Accenture Consultant. Three engagement areas: China market-entry strategy for global liquor clients; Oracle ERP integration and migration for a major electronics manufacturer; revenue-strategy modeling using ML. Cross-cultural delivery at large-org scale.
PwC Consultant. SAP system integration and migration across Greater China clients. Trilingual delivery in English / 中文 / 粵語.
Universidad de los Andes — master's exchange. Latin American economy, accounting rules, and business context. Spanish + Portuguese operating range deepened.
Year-long lead of Niños de Xela — sustainable agricultural-product diversification and long-term business-model design with underprivileged indigenous women in Quetzaltenango. Main speaker and point of contact during in-country fieldwork; organized fundraising events.
Pontificia Universidad Católica de Chile — undergrad exchange. Sharpened cross-cultural operating range and Latin American context for early business-strategy work.
